A Gold Standard Word Alignment for English-Swedish (GES) is a resource containing 1164 manually word aligned sentences pairs from English and Swedish versions of Europarl v. 2.
This is an open dataset of sentences from 19th and 20th century letterpress reprints of documents from the Hussite era. The dataset contains a corpus for language modeling and human annotations for named entity recognition (NER).
This is an open dataset of sentences from 19th and 20th century letterpress reprints of documents from the Hussite era. The dataset contains a corpus for language modeling and human annotations for named entity recognition (NER).
This is an open dataset of scanned images and OCR texts from 19th and 20th century letterpress reprints of documents from the Hussite era. The dataset contains human annotations for layout analysis, OCR evaluation, and language identification.
These are supplementary materials for an open dataset of scanned images and OCR texts from 19th and 20th century letterpress reprints of documents from the Hussite era. The dataset contains human annotations for layout analysis, OCR evaluation, and language identification and is available at http://hdl.handle.net/11234/1-4615. These supplementary materials contain OCR texts from different OCR engines for book pages for which we have both high-resolution scanned images and annotations for OCR evaluation.
A morphological layer for the German part of the SMULTRON corpus. Layer was annotated according to the STTS tagset and the annotation guidelines of the Tiger corpus.
Coordinator: Thomas Müller
Annotators: Francesca Caratti, Arne Recknagel
This distribution contains a morphological layer for the SMULTRON corpus [0].
The annotation process is described in :
@InProceedings{mueller2015,
author = {M\"uller, Thomas and Sch\"utze, Hinrich},
title = {Robust Morphological Tagging with Word Representations},
booktitle = {Proceedings of NAACL},
year = {2015},
}
[0] http://www.cl.uzh.ch/research/parallelcorpora/paralleltreebanks/smultron_en.html
This small dataset contains 3 speech corpora collected using the Alex Translate telephone service (https://ufal.mff.cuni.cz/alex#alex-translate).
The "part1" and "part2" corpora contain English speech with transcriptions and Czech translations. These recordings were collected from users of the service. Part 1 contains earlier recordings, filtered to include only clean speech; Part 2 contains later recordings with no filtering applied.
The "cstest" corpus contains recordings of artificially created sentences, each containing one or more Czech names of places in the Czech Republic. These were recorded by a multinational group of students studying in Prague.
We present a test corpus of audio recordings and transcriptions of presentations of students' enterprises together with their slides and web-pages. The corpus is intended for evaluation of automatic speech recognition (ASR) systems, especially in conditions where the prior availability of in-domain vocabulary and named entities is benefitable.
The corpus consists of 39 presentations in English, each up to 90 seconds long, and slides and web-pages in Czech, Slovak, English, German, Romanian, Italian or Spanish.
The speakers are high school students from European countries with English as their second language.
We benchmark three baseline ASR systems on the corpus and show their imperfection.
Additional three Czech reference translations of the whole WMT 2011 data set (http://www.statmt.org/wmt11/test.tgz), translated from the German originals. Original segmentation of the WMT 2011 data is preserved. and This project has been sponsored by the grants GAČR P406/11/1499 and EuroMatrixPlus (FP7-ICT-2007-3-231720 of the EU and 7E09003+7E11051 of the Ministry of Education, Youth and Sports of the Czech Republic)
This xml file describes the Arabic phonetic constraints are to be applied on Arabic root. The first rule category lists the letters that may not occur in the same root, regardless of their order. The second category lists the letters that may not be used together in a root word with a specific order. The third and fourth categories show that each contiguous letters must not be redundant
ISLRN: 991-445-325-823-5